Introduction

Often academic libraries provide their campus communities with access and information about how to use a wide range of technology products. As learning hubs, they may employ librarians or support specialists who focus on technology needs of students and faculty. However, libraries not only provide access to technology, but also provide access through technology. Many of the systems and projects within these organizations are based on evolving technological infrastructures.

Identifying

Staying up to date with the current technology trends can be challenging, especially for those that don’t make it a priority. When we’re young, learning about new tools often happens organically, through conversations with friends, social media use, or classroom exposure.

For professionals, however, staying informed requires intentional effort. This can include reading journals, attending webinars, curating RSS feeds, or setting aside time to explore new tools and platforms. Lysiak (2020) suggests learning from early adopters, as other institutions try out new technology they will share insights about their successes and pitfalls they may have experienced through blog posts, articles and conferences. It’s important to keep in mind that relying solely on academically published reports during this initial research phase you may already be behind the curve as academic publishing cycles can be quite slow. That said, case studies published in academic journals can still be valuable, as they often focus on specific, practical applications of technology in library settings, offering insight into how new tools are implemented in real-world contexts.

As academic libraries serve diverse departments and majors, the technologies relevant to each field may vary. Identifying tools that are useful across multiple disciplines can be especially useful. Additionally, understanding how and why a particular tool is used by various fields of study enables librarians to provide more targeted services. Cultivating this broad awareness of users’ technology needs is vital to supporting the research and scholarship in higher education environments.

Using

When information professionals understand emerging technology, they are better equipped to assist patrons by explaining tools, facilitating access, and using their own technical knowledge to perform library functions more efficiently.

Libraries and information centers are no longer just housing technology. Increasingly they serve as spaces where their communities can explore and interact with technology directly (Stevens, 2022). In many cases, patrons can check out or license technology items. These may include makerspaces, computer bays, media production rooms, and media centers for viewing, listening or engaging with interactive content.

At the same time, the core systems that support library operations are in and of themselves continually changing technologies. This includes systems managing library information (such as content management systems, e-resource management tools, information retrieval systems, and intranets), internal communication tools (like Microsoft Teams, Zoom, or Google Workspace), and outreach applications (such as library websites and social media platforms), all of which are used by staff on a regular basis (Shih & Holmes-Wong, 2018). The frequency and depth with which professionals need to update their knowledge of these systems may vary by role, however applications are constantly evolving and having a working understanding of changes and alternatives is a vital skill in the LIS field.

Evaluating

Before a library adopts a new technology, it’s advisable to evaluate if the technology is a good fit for their community. Key questions to consider include:

• What dose the technology do?
• Are there limitations?
• What do your patrons need? Does this technology fulfill those needs?
• Are there concerns about privacy, learning, or scalability?

Evaluation methods may include user trials, web analytics, surveys, and interviews. Lysiak (2020) advocates for pilot programs were new technologies can be tried out on a smaller scale before a full library rollout allowing for further exploration and evaluation. An example of this is when the SJSU iSchool provided Coursera membership to a limited number of students for a year, then rolled out the service to the broader student body.

Additionally, white papers can serve as a communication tool that examine and outline potential technology options for internal use or external publication. These documents provide a structured way to analyze and share insights with stakeholders, within the library and beyond.

Evidence

INFO 246: Tech Tools: Text & Data Mining – Text Mining & AI Network Development

The first piece of evidence to show my engagement with emerging technology is a project summery reviewing assignments from the Text & Data Mining class (compH_nnProSummary.pdf). In this course we used Rapid Minor Studio to mine, compile and explore a text corpus using Natural Language Processing (NLP) and Machine Learning (ML) techniques.

Throughout the course our assignments built one on top of the other, from basics like reading excel files into the program to cleaning and analyzing our own corpus, and eventually creating and evaluating a neural network based off of our corpus. My project collected, analyzed, and classified academic job postings from the CSU and UC systems from a two week period. The neural network I created was trained on a random half of the data set; after many attempts it was able to correctly classify the other half of the dataset.

The work done in this class demonstrates my ability to learn new technology, as I had never used Rapid Minor Studio or done anything with NLP or ML before prior to this class. This class allowed me to try a new skill that would normally feel completely out of reach me, as I didn’t have the mathematical or computer science foundations to support this type of exploration, but by using an application with a visual interface and following the models that took us step by step through each process I was able to able to not only create a neural network, but understand how I created it.

INFO 246: Tech Tools: Data Visualization – Visualizing EV Charging Stations

My next piece of evidence that illustrates my engagement with emerging technology is the group project done for Data Visualization (compH_dataViz.pdf). In this project I was paired up with four other students and asked to find and explore a data set that could help us answer questions via visualization techniques learned during the class.

We ended up looking at multiple large data sets to explore the prevalence of EV Charging stations on a macro and micro scale with information covering location and usage in Palo Alto, California and location data across the U.S. Our questions covered geographic, time based, financial, and user profile topics in order to uncover which locations seem to be hot spots for users and speculate why those locations are so successful. As a group we needed to choose which applications we’d be working with which required some evaluation. We considered how much time we all had to spend on the project vs how useful learning a new program would be. We ended up deciding to learn Tableau, a powerful software that none of us had used before.

I primarily worked with the geographic data to create multiple heat maps, tree maps, a distribution map, and a bubble chart in Tableau and google maps.

In order to create my visualizations I needed to be able to work with the datasets in Excel and Tableau; understand and implement best practices for data usage; and the basics of visual design for data. Tableau provided me with an opportunity to learn a new application which was both fun and frustrating. I also needed to learn new skills to work with the datasets in Excel. Other technology that was used during this project includes google chat and zoom for team conversations; google drive to share documents; canvas to create cohesive slides and to add text and graphics to visualizations; Adobe Premiere Pro for presentation editing; and Adobe Acrobat to clean up the final pdf.

This project shows my understanding of how and when to use different applications to create presentations that showcase data visualizations. As big data becomes more prevalent in research institutions, having the skills and knowledge about data visualization tools could be useful; furthermore, many libraries are producing their own data for internal research and advocacy purposes, using these tools can add to the persuasiveness of those documents. This class was my second encounter with data driven research and really solidified my interest in pursuing more technical skills.

INFO 287: Problem Solving with Data – Data Analysis with UNIX, R, & Python

The next piece of evidence that highlights my exploration of emerging technology is my coursework from Problem Solving with Data (compH_dataAnalysis.pdf). In this course we worked with the same dataset, COVID 19 death rates across three different computer environments, UNIX, R, and Python, to perform statistical analysis and data exploration.

Each module of the course built on the last, but instead of progressing within one language, we shifted through them. In UNIX, our work primarily focused on reading, extracting and summarizing data using the command-line. Moving into R, we began filtering results, examining relationships through linear regression, and producing scatter plots with regression lines. I used the libraries tidyverse, GGally, and ggplot2. Finally, in Python we expanded our analysis to include multiple predictors and created more complex visualizations. Here I used Google Colab as the coding environment and the libraries matplotlib and numpy.

This course strengthened my confidence and curiosity with programming and data analysis. It helped me understand not just the mechanics of analysis, but also why a researcher might choose one language or tool over another. These are essential insights for working with research communities. as open access initiatives increasingly include not just publications but datasets as well, being able to evaluate and understand the tools used to work with big data becomes an increasingly important part of supporting the academic mission in research libraries.

ASIS&T Innovation, Disruption, Enquiry, Access (IDEA) Institute on AI – Certificate

The last piece of evidence that shows my engagement with and identification of emerging technology is a Certificate from ASIS&Ts IDEA Institute on AI. In spring 2024, I attended 12 of the institutes sessions on Artificial Intelligence to qualify for the certificate. These sessions lasted roughly an hour a piece and consisted of lectures and short workshops on various aspects of AI from basics to specific use cases.

A major focus of the Institute was the rise of Large Language Models (LLMs), specifically Chat GPT and other generative AI tools. These technologies are one of the biggest trends that LIS organizations are grappling with. Hearing from researchers and professionals about their insights regarding use, ethics, and possible future developments in this area helped me develop a deeper understanding of how these tools work and opened my eyes to various future implementations.

Conclusion

Technology is constantly changing and updating, as a new professional I’m entering the field with the most current knowledge due to my studies. It’s important to keep my eyes open for new tech and be open to learning. This may be critical if I end up working with data science or digital literacy in an academic library.

I plan to set aside time for these explorations and employ the other techniques I found while writing this competency. Additionally, reading broadly, trying out new applications and hardware when I can will be useful in these endeavors.

References

Lysiak, L. (2020). 20th-century innovations: Librarians, trend-watching, and the warning signs of fads. Pennsylvania Libraries, 8(2), 130-137. https://doi.org/10.5195/palrap.2020.232 

Shih, W. & Holmes-Wong, D. (2018). Library information technology. In K. Haycock & B.E. Sheldon (Eds.), The portable MLIS: Insights from the experts (2nd ed., pp. 187-198). Libraries Unlimited.

Stephens, M. (2022). Hyperlinked libraries. In S. Hirsh (Ed.), Information services today: An introduction (3rd ed., pp. 229-239). Rowman & Littlefield Publishers.